Extension of Mean Shift Vector with Theoretical Analysis and Experiment

摘要：

Mean Shift algorithm is a statistics iterativealgorithm which is widely used,its increment(namelyMean Shift vector)of iterative point in each iterationstep changes adaptively.This paper presents anextensional Mean Shift vector,and proves convergenceof Mean Shift Algorithm which using the extensionalMean Shift vector.In addition,we did an experiment----using Mean Shift algorithm to solve the localMaximum of kernel-based density estimation,in ourexperiment,the convergence rate of Mean Shiftalgorithm which using extensional Mean Shift vectorreach twice the convergence rate of Mean Shiftalgorithm which using traditional Mean Shift vector.

作者: Jiaxiang Huang Shaozi Li Changle Zhou

作者单位: Department of Cognitive Science,Xiamen University,Xiamen,China,361005

会议类型: 国际会议

会议名称: 2008 3rd International Conference on Intelligent System and Knowledge Engineering(第三届智能系统与知识工程国际会议)(ISKE 2008)

会议地点: 厦门

会议语种:英文

页码: 1007-1012

在线出版日期: 2008-11-17（万方平台首次上网日期，不代表论文的发表时间）